Laser Rate Equation-Based Filtering for Carrier Recovery in Characterization and Communication

Abstract

Abstract-We formulate a semiconductor laser rate equationbased approach to carrier recovery in a Bayesian filtering framework. Filter stability and the effect of model inaccuracies (unknown or un-useable rate equation coefficients) are discussed. Two potential application areas are explored: laser characterization and carrier recovery in coherent communication. Two rate equation based Bayesian filters, the particle filter and extended Kalman filter, are used in conjunction with a coherent receiver to measure frequency noise spectrum of a photonic crystal cavity laser with less than 20 nW of fiber-coupled output power. The extended Kalman filter is also used to recover a 28 GBd DP-16 QAM signal where a decision-directed phase-locked loop fails.

Continuous variable quantum key distribution with a real local oscillator using simultaneous pilot signals

“…The variable Ω k is a normalized frequency that models a drift of the differential laser frequency as a random walk with variance σ 2 Ω [25]. Additionally, ϕ k is affected by a random walk with variance σ 2 ϕ .…”

Machine Learning Techniques for Optical Performance Monitoring From Directly Detected PDM-QAM Signals

“…Nonlinear phase noise compensation: [18][19][20][21][22] Modulation format identification: [10][11] Optical signal monitoring: [13][14][15] Nonlinearity compensation: [23] Amplitude, phase and nonlinear phase noise: [3][4][5][6][7][8] Optical performance monitoring: [12,[16][17], Nonlinear phase noise compensation: [19,22] Cognitive receiver design:…”

Joint Learning of Laser Relative Intensity and Frequency Noise from Single Experiment and Single Detected Quadrature

“…However, the majority of the proposed methods do not offer an optimum and joint estimation of photon number and optical phase in the presence of the measurement noise. We have recently demonstrated that the techniques from machine learning can be used to perform optimum optical phase detection and thereby enable accurate laser FN characterization 4,5 . The presented framework used Bayesian state-space based inference and employed small signal laser rate equation.…”